Real-time MHE-based nonlinear MPC of a Pendubot system ⋆

نویسندگان

  • M. Gulan
  • M. Salaj
  • M. Abdollahpouri
  • B. Rohaľ-Ilkiv
چکیده

This paper addresses the real-time optimal control of a Pendubot using nonlinear model predictive control (NMPC) combined with nonlinear moving horizon estimation (MHE). This fast, under-actuated nonlinear mechatronic system apparently poses a challenging benchmark problem that may benefit from a nonlinear optimization scheme. To overcome the related computational difficulties we make use of the ACADO Code Generation tool allowing to export a highly efficient Gauss-Newton real-time iteration algorithm tailored to the nonlinear optimal control and estimation problem while respecting the imposed constraints. We show experimental results illustrating the overall closed-loop control performance, as well as the advantages of the nonlinear MHE-based NMPC scheme.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fault Tolerant Model Predictive Control of Quad-Rotor Helicopters with Actuator Fault Estimation

Model predictive control (MPC) at each time step minimizes a cost function subject to dynamical constraints to obtain a stabilizing control signal. Further, MPC is one of the few methodologies that can be used to design feedback control for nonlinear dynamical systems taking into consideration of actuator saturations. It can thus serve as a suitable fault tolerant control approach for quad-roto...

متن کامل

Improved Optimization Process for Nonlinear Model Predictive Control of PMSM

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

متن کامل

A new quadratic programming strategy for efficient sparsity exploitation in SQP-based nonlinear MPC and MHE ?

A large class of algorithms for nonlinear model predictive control (MPC) and moving horizon estimation (MHE) is based on sequential quadratic programming and thus requires the solution of a sparse structured quadratic program (QP) at each sampling time. We propose a novel algorithm based on a dual two-level approach involving a nonsmooth version of Newton’s method that aims at combining sparsit...

متن کامل

Constrained Controller Design for Real-time Delay Recovery in Metro Systems

This study is concerned with the real-time delay recovery problem in metro loop lines. Metro is the backbone of public transportation system in large cities. A discrete event model for traffic system of metro loop lines is derived and presented. Two effective automatic controllers, linear quadratic regulator (LQR) and model predictive controller (MPC), are used to recover train delays. A newly-...

متن کامل

A Fast Moving Horizon Estimation Algorithm Based on Nonlinear Programming Sensitivity

Moving Horizon Estimation (MHE) is an efficient optimization-based strategy for state estimation. Despite the attractiveness of this method, its application in industrial settings has been rather limited. This has been mainly due to the difficulty to solve, in real-time, the associated dynamic optimization problems. In this work, a fast MHE algorithm able to overcome this bottleneck is proposed...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015